code: def test_multiple_ts(self):
      dim = 2
  
      # simple test
      multi_ts_1 = [self.series1 + 1, self.series1 + 1]
      multi_ts_2 = [self.series1 + 2, self.series1 + 1]
      assert (
          metrics.rmse(
              multi_ts_1,
              multi_ts_2,
              reduction=np.mean,
              inter_reduction=np.mean,
          )
          == 0.5
      )
  
      # checking univariate, multivariate and multi-ts gives same metrics with same values
      series11 = self.series1.stack(self.series1) + 1
      series22 = self.series2.stack(self.series2)
      multi_1 = [series11] * dim
      multi_2 = [series22] * dim
  
      test_metric = [
          metrics.r2_score,
          metrics.rmse,
          metrics.mape,
          metrics.smape,
          metrics.mae,
          metrics.coefficient_of_variation,
          metrics.ope,
          metrics.marre,
          metrics.mse,
          metrics.rmsle,
      ]
  
      for metric in test_metric:
          assert metric(self.series1 + 1, self.series2) == metric(
              series11, series22
          )
          np.testing.assert_array_almost_equal(
              np.array([metric(series11, series22)] * 2),
              np.array(metric(multi_1, multi_2)),
          )
  
      # trying different functions
      shifted_1 = self.series1 + 1
      shifted_2 = self.series1 + 2
      shifted_3 = self.series1 + 3
  
      assert metrics.rmse(
          [shifted_1, shifted_1],
          [shifted_2, shifted_3],
          reduction=np.mean,
          inter_reduction=np.max,
      ) == metrics.rmse(shifted_1, shifted_3)
  
      # checking if the result is the same with different n_jobs and verbose True
      assert metrics.rmse(
          [shifted_1, shifted_1],
          [shifted_2, shifted_3],
          reduction=np.mean,
          inter_reduction=np.max,
      ) == metrics.rmse(
          [shifted_1, shifted_1],
          [shifted_2, shifted_3],
          reduction=np.mean,
          inter_reduction=np.max,
          n_jobs=-1,
          verbose=True,
      )
  
imports: import numpy
  import pandas
  import pytest
  from darts import TimeSeries
  from darts.metrics import metrics
label_desc: Use image node_id 23 for calling the TestMetrics obj's underlying member method code with example usage: obj.test_multiple_ts() without return types